Introduction
Control efforts against schistosomiasis are hampered by the subjective interpretation of the point-of-care circulating cathodic antigen (POC-CCA) urine test, which limits diagnostic consistency. We developed MEDSCAN (Mobile-Enabled Diagnostics for Schistosomiasis Control Analytics), a mobile application that uses smartphone imaging and computer vision to automate POC-CCA interpretation.
Methods
In a multi-site laboratory evaluation across the USA, the Netherlands, and Kenya, we compared MEDSCAN to visual G-Score interpretation and a benchtop lateral flow reader (LFR).
Results
All three methods produced clear concentration–response relationships, with normalized machine-based metrics achieving AUROC ≥ 0.90. MEDSCAN demonstrated excellent inter-user reproducibility (intra-class correlation coefficients exceeding 0.94) and substantial agreement with both visual and LFR interpretations across sites. Some device-to-device variability was observed, attributable to differences in smartphone camera hardware and image processing; however, binary diagnostic outcomes remained robust across a heterogeneous set of smartphones.
Discussion
These results establish operational positivity thresholds for MEDSCAN—based on test-line signal alone or normalized metrics—suitable for direct implementation in field surveillance workflows. A large-scale field study is underway to evaluate MEDSCAN under routine POC-CCA surveillance conditions in endemic settings.